Utilization of SVM, LSSVM and GP for predicting the medical waste generation

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The prediction of wastes generated in the hospital will help their management for several activities like storage, transport and disposing. This chapter adopts Support Vector Machine (SVM), Least Square Support Vector Machine (LSSVM) and Genetic Programming (GP) in order to estimate the rate of medical waste generation. In the event of predicting the rate, type of hospital, capacity and bed occupancy has been used as inputs of SVM, LSSVM and GP. SVM is based on statistical learning theory, which provides an elegant tool for nonlinear system modeling. LSSVM is the re-formulation to the general SVM. GP, a best part of evolutionary algorithm and also the specification of Genetic Algorithm (GA). These SVM, LSSVM and GP have been used as the regression techniques. The results show the performance of the developed SVM, LSSVM and GP models were elegant and outstanding. © 2020, IGI Global. © 2020 by IGI Global. All rights reserved.

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AlanDeğerDil
dc.contributor.authorJagan, J.
dc.contributor.authorDalkiliç, Yildirim
dc.contributor.authorSamui, Pijush
dc.date.accessioned2026-10-18T20:28:21.844205235Z
dc.date.available2026-10-18T20:28:21.844205235Z
dc.date.issued2019
dc.description.abstractThe prediction of wastes generated in the hospital will help their management for several activities like storage, transport and disposing. This chapter adopts Support Vector Machine (SVM), Least Square Support Vector Machine (LSSVM) and Genetic Programming (GP) in order to estimate the rate of medical waste generation. In the event of predicting the rate, type of hospital, capacity and bed occupancy has been used as inputs of SVM, LSSVM and GP. SVM is based on statistical learning theory, which provides an elegant tool for nonlinear system modeling. LSSVM is the re-formulation to the general SVM. GP, a best part of evolutionary algorithm and also the specification of Genetic Algorithm (GA). These SVM, LSSVM and GP have been used as the regression techniques. The results show the performance of the developed SVM, LSSVM and GP models were elegant and outstanding. © 2020, IGI Global. © 2020 by IGI Global. All rights reserved.
dc.identifier.doi10.4018/978-1-7998-0948-7.ch038
dc.identifier.endpage829
dc.identifier.isbn978-179980949-4; 978-179980948-7
dc.identifier.scopus2-s2.0-85125611397
dc.identifier.startpage808
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/ebyu/13530
dc.language.isoen
dc.publisherIGI Global
dc.relation.ispartofSustainable Infrastructure: Breakthroughs in Research and Practice
dc.rightsinfo:eu-repo/semantics/openAccess
dc.titleUtilization of SVM, LSSVM and GP for predicting the medical waste generation
dc.typeBook Chapter
dspace.entity.typePublication
rdl.citation.scopus0
rdl.source.indexSCOPUS